A Comparative Study About Identification Method For The Rice Wine Originated From Different Areas

This topic is analysis the rice wine that produced in different places by electronic nose, GC-MS andphysical indicators. Firstly, the electronic nose analysis the rice wine that produced in different places,Artificial Neural Networks（ANN）and principal components analysis（PCA）were used as date analysisin order to find the best data processing and analysis method. Secondly, the impact correlation detectionindicators of rice wine years and produced places were expected to find combined with GC-MS techniquefor the separation of each component ingredients, qualitative and semi-quantitative analysis. Finally,physical indicators (alcohol content, total sugar, pH, total acid) were measured according to rice winenational standards, and using MATLAB software to fit the data obtained in order to obtain physical andchemical indicators and wine producing area, wine age correlation between the mathematical model forthe origin of wine, wine age determination to provide a theoretical reference. The three differentcomparative analysis methods were expect to establish a scientific evaluation system, improve thedetection efficiency and reduce testing costs, and eliminate artificial sensory evaluation of possible errors,increase the detection accuracy of the data. The results as follows:The accurately identify of Artificial Neural Networks（ANN）was98.8%, the test set correctrecognition rate of82.4%, two of which of them can be achieved better predict result. Whereas, in theprincipal components analysi（sPCA）discriminant model, Shaoxing rice wine Gls, non Shaoxing rice wineGls, as well as non-geographical indications outside Shaoxing rice wine samples were occupying differentpositions; GIs Shaoxing Shaoxing rice wine and rice wine each non-geographical indications have agreater relatively concentrated distribution range, there is a certain edge intersection, PC1accounted80.396%, PC2accounted6.092%, PC3accounted4.962%, the three factors accounted91.45%. Thisindicated that the differences were impact by this three factors and PC1is the most important factor.Secondly, GC-MS was used to analysis the main ingredient in rice wine aroma, aroma components fromthe total ion chromatogram can be seen, the five chemicals materials of rice wine alcohols, esters,aldehydes, acids and ketones occupied most proportion, through different habitats and ages of wineanalysis of these five substances derived contrast, the main aroma components in esters, followed by thealcohol. Finally, according to national wine standards for different areas of the same wine wine age, forthe four physical indicators of total sugar, total acidity, alcohol content and pH were detected, and their relationship between wine age and place of origin were found.